The proliferation of processor implemented control of non-computing devices, in both the public context (e.g., streetlights, traffic signals, electrical meters) and the home (e.g., internet connected lights, home automation systems, media streaming platforms), sometimes referred to as the “Internet of Things” (IoT) presents, at a minimum, a vast, largely untapped opportunity for the collection and processing of data at previously unimaginable scale and levels of granularity. For example, the controllers used in certain IoT home automation systems may, during the course of their intended operation, spend the bulk of their time monitoring and collecting temperatures inside and outside of a house. While monitoring and recording temperature data is typically not computationally expensive, as such, does not require a powerful processor, an IoT controller may, nonetheless possess substantial processing and memory resources to support occasional, computationally demanding operations, such as voice recognition.
A modern home may have multiple devices having similar sensor technology and processing capabilities as the home automation controller described above. Taken together, these devices can potentially be used to collect a wealth of highly granular data as to their environment (for example, block by block temperature data), as well as unused processing capacity to analyze and process such data. Beyond the possibilities for data science and mining data on massive scales, the ability to orchestrate and collectivize the processing power of a cloud or “fog” of small, networked processors presents new opportunities to extend the useful life of legacy devices, such as older personal computers, tablets, and phones, whose processing and data collection resources, while perhaps no longer suitable to support applications on subsequent generations of the same devices, could still be usefully applied as part of a larger processing network. Further applications of secure distributed processing across networks of heterogeneous processing nodes include, without limitation, providing CPU power to support proof-of-work based systems for verifying transactions recorded in a distributed ledger.
Realizing this wealth of unused computational power and sensor data presents significant technical challenges, including without limitation, orchestration issues (e.g., breaking up a processing task among numerous small processors) and security issues, such as protecting users' privacy and guarding against misuse of devices' sensors and processing capabilities, such as by surreptitiously recording conversations inside a house, or coopting a device's processing resources and network connection (e.g., turning the device into a “spambot.”)
Embodiments as disclosed and claimed herein address these technical challenges by providing systems and methods for secure distributed processing across networks of heterogeneous processing nodes.